Testing the white noise hypothesis of stock returns
Testing the white noise hypothesis of stock returns
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检验股票收益的白噪声假设
DOI：
10.1016/j.econmod.2018.08.003
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发表时间：
2019
影响因子：
4.7
通讯作者：
Jonathan B. Hill and Kaiji Motegi
中科院分区：
文献类型：
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作者：
Jonathan B. Hill and Kaiji Motegi
股票市场的弱式有效性意味着股票收益在时间序列意义上的不可预测性，而后者主要在序列独立性或鞅差假设下进行检验。由于这些性质排除了股票收益率中可能存在的弱相关性，因此检验收益率是否为白色噪声是很有意义的。我们执行白色噪声测试的Shao（2011）块wild bootstrap的帮助下。我们发现，在滚动窗口中，块结构在自举置信带中记录了人工周期性。我们通过随机化块大小来消除周期性。白色噪声假说在中国和日本市场上被接受，表明这些市场是弱式有效的。对于英国，白色噪声假设被拒绝。而美国市场在伊拉克战争和次贷危机期间由于显著的负自相关性，表明这些市场在危机时期是无效的。
Weak form efficiency of stock markets implies unpredictability of stock returns in a time series sense, and the latter is tested predominantly under a serial independence or martingale difference assumption. Since these properties rule out weak dependence that may exist in stock returns, it is of interest to test whether returns are white noise. We perform white noise tests assisted by Shao's (2011) blockwise wild bootstrap. We reveal that, in rolling windows, the block structure inscribes an artificial periodicity in bootstrapped confidence bands. We eliminate the periodicity by randomizing a block size. The white noise hypothesis is accepted for Chinese and Japanese markets, suggesting that those markets are weak form efficient. The white noise hypothesis is rejected for U.K. and U.S. markets during the Iraq War and the subprime mortgage crisis due to significantly negative autocorrelations, suggesting that those markets are inefficient in crisis periods.